Efficient Identification in Linear Structural Causal Models with Auxiliary Cutsets
Daniel Kumor, Carlos Cinelli, Elias Bareinboim
2020年份
21被引次数
7顶会引用
摘要
We develop a a new polynomial-time algorithm for identification of structural coefficients in linear causal models that subsumes previous stateof-the-art methods, unifying several disparate approaches to identification in this setting. Building on these results, we develop a procedure for identifying total causal effects in linear systems.
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引用它的顶会 Paper7
- On the Parameter Identifiability of Partially Observed Linear Causal ModelsXinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun 等NeurIPS 2024 · 被引用 9 次
- Causal Effect Identification in LiNGAM Models with Latent ConfoundersDaniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar, Mathias Drton 等ICML 2024 · 被引用 8 次
- Counterfactual Identification Under Monotonicity ConstraintsAurghya Maiti, Drago Plecko, Elias BareinboimAAAI 2025 · 被引用 4 次
- On the Complexity of Identification in Linear Structural Causal ModelsJulian Dörfler, Benito van der Zander, Markus Bläser, Maciej LiskiewiczNeurIPS 2024 · 被引用 4 次
- Identification for Tree-Shaped Structural Causal Models in Polynomial TimeAaryan Gupta, Markus BläserAAAI 2024 · 被引用 1 次
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